PROJECT SUMMARY This proposal is to develop MELD, a computational Bayesian accelerator that ?melds? together molecular dynamics simulations with external knowledge. It is novel in harnessing information that has not been usable before ? because it is too sparse, noisy, ambiguous, combinatoric, or too corrupted for traditional approaches. In contrast to the high-certainty restraints traditionally used in MD simulations, MELD leverages a much broader range of real-world high-uncertainty restraints. The first specific aim is to incorporate such information in protein structure determination, in several collaboration projects with experimentalists who perform solution x-ray scattering, ESR, and high-throughput alanine scanning structures of peptide protein complexes. The second aim is to also harness information about processes, trajectories, and dynamic routes to speed the identification of protein states. MELD promises to extend physics-based simulations for determining larger protein structures, for folding larger proteins, for binding more flexible ligands, and for exploring larger mechanistic actions, than current MD simulation methods can handle.